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+++ b/README.md
@@ -5,10 +5,39 @@
 
 Canonically pronouced *nice*
 
-A compositional statistics and visualization toolbox
 
-You can install Gneiss via pip
+ compositional statistics and visualization toolbox
++gneiss is a compositional statistics and visualization toolbox.  
+ 
+Note that gneiss is not compatible with python 2, and is compatible with Python 3.4 or later.
+gneiss is currently in alpha.  We are actively developing it, and __backward-incompatible interface changes can and will arise__.
+
+# Installation
+
+To install this package, it is recommended to use conda as follows
+
+```
+conda install -c biocore gneiss
+```
+
+You can also install Gneiss via pip
 
 ```
 pip install gneiss
 ```
+
+To run through the tutorials, you'll need a few more packages, namely `seaborn`, `biom-format` and `h5py`.
+These packages can be installed with conda as follows
+```
+source activate gneiss
+conda install seaborn h5py
+pip install biom-format
+```
+
+# Examples
+
+IPython notebooks demonstrating some of the modules in gneiss can be found as follows
+
+* [What are balances](https://github.com/biocore/gneiss/blob/master/ipynb/balance_trees.ipynb)
+* [Linear regression on balances](https://github.com/biocore/gneiss/blob/master/ipynb/88soils.ipynb)
+